"To prevent this rare but critical condition, scientists at Northwestern University and Ann & Robert H. Lurie Children's Hospital of Chicago developed and validated AI models that accurately identify children at high risk for sepsis within 48 hours, so they can receive early preemptive care, as detailed in a study published in JAMA Pediatrics. These predictive models used routine electronic health record (EHR) data from the first four hours the child spent in the emergency department before organ dysfunction was present."
""The predictive models we developed are a huge step toward precision medicine for sepsis in children," said corresponding author Elizabeth Alpern, MD, MSCE, vice chair and chief of Emergency Medicine in the Department of Pediatrics. "These models showed robust balance in identifying children in the emergency department who will later develop sepsis, without overidentifying those who are not at risk. This is very important because we want to avoid aggressive treatment for children who don't need it.""
AI models were developed and validated across five health systems contributing to the Pediatric Emergency Care Applied Research Network (PECARN) using routine electronic health record data captured during the first four hours in the emergency department. Models predict which children are likely to develop sepsis within 48 hours using the Phoenix Sepsis Criteria. Discovery used retrospective ED visits from January 2016 to February 2020 and validation applied the models to 2021–2022 visits. Models demonstrated robust balance by identifying children who later developed sepsis while avoiding overidentification of low-risk children, enabling early preemptive care and reducing unnecessary aggressive treatment.
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